Article Text

Download PDFPDF
Original research
Derivation and validation of a predictive model for advanced colorectal neoplasia in asymptomatic adults
  1. Thomas F Imperiale1,2,3,
  2. Patrick O Monahan4,
  3. Timothy E Stump4,
  4. David F Ransohoff5
  1. 1 Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
  2. 2 Center for Innovation, Health Services Research and Development, Richard L Roudebush VA Medical Center, Indianapolis, IN, USA
  3. 3 The Regenstrief Institute Inc, Indianapolis, IN, USA
  4. 4 Department of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, USA
  5. 5 Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
  1. Correspondence to Dr Thomas F Imperiale, Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA; timperia{at}iu.edu

Abstract

Objective Knowing risk for advanced colorectal neoplasia (AN) could help patients and providers choose among screening tests, improving screening efficiency and uptake. We created a risk prediction model for AN to help decide which test might be preferred, a use not considered for existing models.

Design Average-risk 50-to-80-year olds undergoing first-time screening colonoscopy were recruited from endoscopy units in Indiana. We measured sociodemographic and physical features, medical and family history and lifestyle factors and linked these to the most advanced finding. We derived a risk equation on two-thirds of the sample and assigned points to each variable to create a risk score. Scores with comparable risks were collapsed into risk categories. The model and score were tested on the remaining sample.

Results Among 3025 subjects in the derivation set (mean age 57.3 (6.5) years; 52% women), AN prevalence was 9.4%. The 13-variable model (c-statistic=0.77) produced three risk groups with AN risks of 1.5% (95% CI 0.72% to 2.74%), 7.06% (CI 5.89% to 8.38%) and 27.26% (CI 23.47% to 31.30%) in low-risk, intermediate-risk and high-risk groups (p value <0.001), containing 23%, 59% and 18% of subjects, respectively. In the validation set of 1475 subjects (AN prevalence of 8.4%), model performance was comparable (c-statistic=0.78), with AN risks of 2.73% (CI 1.25% to 5.11%), 5.57% (CI 4.12% to 7.34%) and 25.79% (CI 20.51% to 31.66%) in low-risk, intermediate-risk and high-risk subgroups, respectively (p<0.001), containing proportions of 23%, 59% and 18%.

Conclusion Among average-risk persons, this model estimates AN risk with high discrimination, identifying a lower risk subgroup that may be screened non-invasively and a higher risk subgroup for which colonoscopy may be preferred. The model could help guide patient–provider discussions of screening options, may increase screening adherence and conserve colonoscopy resources.

  • cancer prevention
  • colorectal cancer screening
  • colonoscopy

Data availability statement

Data are available upon reasonable request.

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Data availability statement

Data are available upon reasonable request.

View Full Text

Footnotes

  • Contributors TFI—planning, conduct, analysis, drafting and critical revision of the manuscript; POM—analysis, drafting and critical revision of the manuscript; TES—analysis, drafting and critical revision of the manuscript; DFR—planning, drafting and critical revision of the manuscript; Curlie Morrow—project management; Kimberly Hemmerlein and Mungai Maina (Research Assistants)—data collection; Janetta Matesan—data management.

  • Funding This work was supported by the National Cancer Institute (R01-CA104459); the Walther Cancer Institute, Indianapolis, IN; The Indiana University Melvin and Bren Simon Cancer Center; and a project development team within the Indiana Clinical and Translational Sciences Institute (grant UL1TR001108) from the National Center for Research Resources, National Institutes of Health, Indianapolis, IN.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.